Tactile Sensing System Based on Arrays of Graphene Woven Microfabrics: Electromechanical Behavior and Electronic Skin Application

TLDR

Nanomaterials, particularly graphene woven fabrics, provide a promising balance of high sensitivity and stretchability for strain sensing due to their unique electromechanical properties. This study investigates how the network configuration of graphene woven fabrics can deliver highly sensitive strain sensing while preserving resistance stability. Experiments and simulations show that the graphene woven fabric achieves a gauge factor of 500 at 2 % strain, stretchability exceeding 40 % by tuning growth parameters, and its sensors effectively detect human motion, sound signals, and spatial stress distributions.

Abstract

Nanomaterials serve as promising candidates for strain sensing due to unique electromechanical properties by appropriately assembling and tailoring their configurations. Through the crisscross interlacing of graphene microribbons in an over-and-under fashion, the obtained graphene woven fabric (GWF) indicates a good trade-off between sensitivity and stretchability compared with those in previous studies. In this work, the function of woven fabrics for highly sensitive strain sensing is investigated, although network configuration is always a strategy to retain resistance stability. The experimental and simulation results indicate that the ultrahigh mechanosensitivity with gauge factors of 500 under 2% strain is attributed to the macro-woven-fabric geometrical conformation of graphene, which induces a large interfacial resistance between the interlaced ribbons and the formation of microscale-controllable, locally oriented zigzag cracks near the crossover location, both of which have a synergistic effect on improving sensitivity. Meanwhile, the stretchability of the GWF could be tailored to as high as over 40% strain by adjusting graphene growth parameters and adopting oblique angle direction stretching simultaneously. We also demonstrate that sensors based on GWFs are applicable to human motion detection, sound signal acquisition, and spatially resolved monitoring of external stress distribution.